{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# 第八讲:求解$Ax=b$:可解性和解的结构\n", "\n", "举例,同上一讲:$3 \\times 4$矩阵\n", "$\n", "A=\n", "\\begin{bmatrix}\n", "1 & 2 & 2 & 2\\\\\n", "2 & 4 & 6 & 8\\\\\n", "3 & 6 & 8 & 10\\\\\n", "\\end{bmatrix}\n", "$,求$Ax=b$的特解:\n", "\n", "写出其增广矩阵(augmented matrix)$\\left[\\begin{array}{c|c}A & b\\end{array}\\right]$:\n", "\n", "$$\n", "\\left[\n", "\\begin{array}{c c c c|c}\n", "1 & 2 & 2 & 2 & b_1 \\\\\n", "2 & 4 & 6 & 8 & b_2 \\\\\n", "3 & 6 & 8 & 10 & b_3 \\\\\n", "\\end{array}\n", "\\right]\n", "\\underrightarrow{消元}\n", "\\left[\n", "\\begin{array}{c c c c|c}\n", "1 & 2 & 2 & 2 & b_1 \\\\\n", "0 & 0 & 2 & 4 & b_2-2b_1 \\\\\n", "0 & 0 & 0 & 0 & b_3-b_2-b_1 \\\\\n", "\\end{array}\n", "\\right]\n", "$$\n", "\n", "显然,有解的必要条件为$b_3-b_2-b_1=0$。\n", "\n", "讨论$b$满足什么条件才能让方程$Ax=b$有解(solvability condition on b):当且仅当$b$属于$A$的列空间时。另一种描述:如果$A$的各行线性组合得到$0$行,则$b$端分量做同样的线性组合,结果也为$0$时,方程才有解。\n", "\n", "解法:令所有自由变量取$0$,则有$\n", "\\Big\\lbrace\n", "\\begin{eqnarray*}\n", "x_1 & + & 2x_3 & = & 1 \\\\\n", " & & 2x_3 & = & 3 \\\\\n", "\\end{eqnarray*}\n", "$\n", ",解得\n", "$\n", "\\Big\\lbrace\n", "\\begin{eqnarray*}\n", "x_1 & = & -2 \\\\\n", "x_3 & = & \\frac{3}{2} \\\\\n", "\\end{eqnarray*}\n", "$\n", ",代入$Ax=b$求得特解\n", "$\n", "x_p=\n", "\\begin{bmatrix}\n", "-2 \\\\ 0 \\\\ \\frac{3}{2} \\\\ 0\n", "\\end{bmatrix}\n", "$。\n", "\n", "令$Ax=b$成立的所有解:\n", "\n", "$$\n", "\\Big\\lbrace\n", "\\begin{eqnarray}\n", "A & x_p & = & b \\\\\n", "A & x_n & = & 0 \\\\\n", "\\end{eqnarray}\n", "\\quad\n", "\\underrightarrow{两式相加}\n", "\\quad\n", "A(x_p+x_n)=b\n", "$$\n", "\n", "即$Ax=b$的解集为其特解加上零空间,对本例有:\n", "$\n", "x_{complete}=\n", "\\begin{bmatrix}\n", "-2 \\\\ 0 \\\\ \\frac{3}{2} \\\\ 0\n", "\\end{bmatrix}\n", "+\n", "c_1\\begin{bmatrix}-2\\\\1\\\\0\\\\0\\\\\\end{bmatrix}\n", "+\n", "c_2\\begin{bmatrix}2\\\\0\\\\-2\\\\1\\\\\\end{bmatrix}\n", "$\n", "\n", "对于$m \\times n$矩阵$A$,有矩阵$A$的秩$r \\leq min(m, n)$\n", "\n", "列满秩$r=n$情况:\n", "$\n", "A=\n", "\\begin{bmatrix}\n", "1 & 3 \\\\\n", "2 & 1 \\\\\n", "6 & 1 \\\\\n", "5 & 1 \\\\\n", "\\end{bmatrix}\n", "$\n", ",$rank(A)=2$,要使$Ax=b, b \\neq 0$有非零解,$b$必须取$A$中各列的线性组合,此时A的零空间中只有$0$向量。\n", "\n", "行满秩$r=m$情况:\n", "$\n", "A=\n", "\\begin{bmatrix}\n", "1 & 2 & 6 & 5 \\\\\n", "3 & 1 & 1 & 1 \\\\\n", "\\end{bmatrix}\n", "$\n", ",$rank(A)=2$,$\\forall b \\in R^m都有x \\neq 0的解$,因为此时$A$的列空间为$R^m$,$b \\in R^m$恒成立,组成$A$的零空间的自由变量有n-r个。\n", "\n", "行列满秩情况:$r=m=n$,如\n", "$\n", "A=\n", "\\begin{bmatrix}\n", "1 & 2 \\\\\n", "3 & 4 \\\\\n", "\\end{bmatrix}\n", "$\n", ",则$A$最终可以化简为$R=I$,其零空间只包含$0$向量。\n", "\n", "总结:\n", "\n", "$$\\begin{array}{c|c|c|c}r=m=n&r=n\\lt m&r=m\\lt n&r\\lt m,r\\lt n\\\\R=I&R=\\begin{bmatrix}I\\\\0\\end{bmatrix}&R=\\begin{bmatrix}I&F\\end{bmatrix}&R=\\begin{bmatrix}I&F\\\\0&0\\end{bmatrix}\\\\1\\ solution&0\\ or\\ 1\\ solution&\\infty\\ solution&0\\ or\\ \\infty\\ solution\\end{array}$$" ] } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "Python [default]", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.5.2" } }, "nbformat": 4, "nbformat_minor": 0 }